Applied multivariate statistics with...
SpringerLink (Online service)

 

  • Applied multivariate statistics with R[electronic resource] /
  • 紀錄類型: 書目-語言資料,印刷品 : Monograph/item
    杜威分類號: 519.535
    書名/作者: Applied multivariate statistics with R/ by Daniel Zelterman.
    作者: Zelterman, Daniel.
    出版者: Cham : : Springer International Publishing :, 2015.
    面頁冊數: xvi, 393 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Multivariate analysis.
    標題: Mathematical statistics.
    標題: R (Computer program language)
    標題: Statistics.
    標題: Statistics for Life Sciences, Medicine, Health Sciences.
    標題: Biostatistics.
    標題: Epidemiology.
    標題: Bioinformatics.
    標題: Systems Biology.
    ISBN: 9783319140933
    ISBN: 9783319140926
    內容註: Introduction -- Elements of R -- Graphical Displays -- Basic Linear Algebra -- The Univariate Normal Distribution -- Bivariate Normal Distribution -- Multivariate Normal Distribution -- Factor Methods -- Multivariate Linear Regression -- Discrimination and Classification -- Clustering -- Time Series Models -- Other Useful Methods -- References -- Appendix -- Selected Solutions -- Index.
    摘要、提要註: This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the Behavior Risk Factor Surveillance System, discussing both the shortcomings of the data as well as useful analyses. The text avoids theoretical derivations beyond those needed to fully appreciate the methods. Prior experience with R is not necessary. .
    電子資源: http://dx.doi.org/10.1007/978-3-319-14093-3
評論
Export
取書館別
 
 
變更密碼
登入